Radiometric Non-Uniformity Characterization and Correction of Landsat 8 OLI Using Earth Imagery-Based Techniques

Remote Sensing

Frank Pesta¹  Suman Bhatta²  Dennis Helder²  Nischal Mishra²  Brian Markham²  James C. Storey²  Ron Morfitt² 

[1] Image Processing Lab, Department of Electrical Engineering and Computer Science, South Dakota State University, 315 Daktronics Hall, P.O. Box 2219 Brookings, SD 57007, USA;

关键词: side-slither;    relative gain;    radiometric calibration;    Landsat 8;    OLI;    deep convective clouds;    yaw maneuver;   

DOI  :  10.3390/rs70100430

来源: mdpi

【 摘 要 】

Landsat 8 is the first satellite in the Landsat mission to acquire spectral imagery of the Earth using pushbroom sensor instruments. As a result, there are almost 70,000 unique detectors on the Operational Land Imager (OLI) alone to monitor. Due to minute variations in manufacturing and temporal degradation, every detector will exhibit a different behavior when exposed to uniform radiance, causing a noticeable striping artifact in collected imagery. Solar collects using the OLI’s on-board solar diffuser panels are the primary method of characterizing detector level non-uniformity. This paper reports on an approach for using a side-slither maneuver to estimate relative detector gains within each individual focal plane module (FPM) in the OLI. A method to characterize cirrus band detector-level non-uniformity using deep convective clouds (DCCs) is also presented. These approaches are discussed, and then, correction results are compared with the diffuser-based method. Detector relative gain stability is assessed using the side-slither technique. Side-slither relative gains were found to correct streaking in test imagery with quality comparable to diffuser-based gains (within 0.005% for VNIR/PAN; 0.01% for SWIR) and identified a 0.5% temporal drift over a year. The DCC technique provided relative gains that visually decreased striping over the operational calibration in many images.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.